Journal
CHEMOSPHERE
Volume 277, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chemosphere.2021.130260
Keywords
Arsenic; Lake sediments; Risk assessment; Fraction transformation; DGH model
Categories
Funding
- National Natural Science Foundation of China [41877368, 41701546, 41877471]
- Youth Innovation Promotion Association CAS [2017059]
- State Key Joint Laboratory of Environment Simulation and Pollution Control [20L03ESPC]
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The study investigated arsenic pollution in surface sediments using the DGH model, showing low contamination and ecological risk levels in total content but low to moderate risk in the fraction. Dynamic risk assessment revealed potential DGH burst trends in 45.24%-78.57% of the BYD Lake.
The fraction transformation from stable to mobile forms in sediments is continuous, slow, and spontaneous chain reactions causing static risks to the aquatic system. However, this process may change into abrupt, rapid, and dynamic paths when certain physicochemical conditions changed. Using the Delayed Geochemical Hazard (DGH) model, comprehensive methods combing both static and dynamic risk assessment were therefore conducted to evaluate the aforementioned processes. By applying these methods, arsenic (As) pollution in surface sediments of the Baiyangdian Lake (BYD Lake) was investigated thoroughly as a case study area. The results showed that the total As concentrations in those sediment samples ranged from 4.87 to 17.94 mg/kg, with an average of 8.75 mg/kg. In a fraction, Fe and Mn were observed to pose effects on the surface-adsorbed (AsS) and residual fractions (AsR) with the coefficient analysis. The static risk assessment showed that both the contamination and ecological risk are at a low level in the total content but a low to moderate risk in the fraction. The dynamic risk assessment posted the potential transformation paths of As in the sediments, indicating a trend of potential DGH burst in 45.24%-78.57% of the BYD Lake. In summary, this study provides a methodology for the risk assessment of arsenic that may extend to other heavy metal(loid)s combining static and dynamic processes in sediments. (C) 2021 Elsevier Ltd. All rights reserved.
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